eMiRo: an ontology-based system for clinical data integration and analysis

Biological experiments and bioinformatics analysis are producing large datasets of omics data (e.g. genomics, proteomics, interac-tomics, etc.), stored in diversified sources and databases. Biological data and bioinformatics results can be related to various information, such as clinical data (e.g. cancer stage) or environment data (e.g. place where a patient lives), but this requires novel data integration mechanisms and analysis algorithms. Novel data structures are needed for data integration, while efficient algorithms are necessary for managing integrated data and to analyze results in order to extract knowledge and underline correlation with environmental factors. In this paper an ontology-based system for clinical data integration and analysis is presented. The system, called eMiRo (Electronic MedIcal RecOrd), includes geo-reference features for epidemiological analysis based on geographical and clinical information. Using eMiRo, a physician is able to handle and integrate biological data; moreover, the system supports the retrieval of additional information such as ontology terms and information about genes and diseases. When conducting a study, for each gene relevant to the study, biological function and relations with other genes as well as involvement in biological processes is reported.